[Summary: Local by Social author Andy Gibson is working on a new paper for NESTA on how digital innovation can save public services, and has asked for reflections on ‘obstacles and their solutions’ to adoption or more social technology. I’ve written on practical barriers to digital technology in government before, but here I’m exploring an economic argument that sets out a potential challenge to many digital-social innovation projects*.]
The Pareto Problem
The Pareto Principle (named after the famous Italian Economist, but often known just as the 80-20 rule) suggests that in many real-world situations 80% of the features required in a project can be gained with just 20% of the effort**.
In software development and much of the business world, focussing on the 80% of features you can build easily makes sense. For each bit of effort put in at the start there is a large marginal return and benefit; but as you get to the trickier bits of a project, the marginal benefit (the number of people who will use a feature; how much benefit each new feature will bring etc.) relative to effort put in falls. The last 20% of features might cost four times as much as the first 80%, and in many cases, implementing them simply isn’t cost effective. So, the rational developer or manager never provides them.
Public Services don’t work like that. The tricky 20% of a service to provide is often the service to the most in need. Into that tricky 20% might fall providing services in remote rural areas; educating children from more challenging backgrounds; providing transports services for the elderly; making sure education classes are accessible to those with additional needs and so-on. When social innovators hold up technology driven innovations – new ways of providing public services – we have to ask: are they just solving the easy 80% and ignoring the tough cases?
Is the promise of more efficient and cheaper digital services simply the result of a slight-of-hand – measuring the costs of a service based on it’s provision in the easy cases and bracketing out the tough cases which would require re-engineering systems and adding significant cost and effort if a digital service were to be a universal service?
Possible Solutions
The Pareto Problem isn’t an argument against digital innovation per se. Innovation can shift where the Pareto Problem kick’s in (e.g. Can we serve 90% of the people on 10% of the cost and make savings that way?) and innovation can help the public sector to challenge the frequent over-design of processes and systems around the tough cases. However, the Pareto Problem is significant. A few possible ways to address it in thinking about digital innovation are addressed below.
- Account for a universal service – any digital innovation needs to show its cost and benefits not just in the easy pilot cases – but also if it were to provide a universal service. Or if it can’t provide a universal service it needs to explain it’s limitations, and allow the public sector to properly cost provision to those the innovation will not work for.
- Take the tough cases into account – Conventional design of services in the public sector often starts with tough cases. Staff have in mind the cases they faced recently where a service user had complex needs – and they design from the tricky cases first – building all sorts of processes and systems to cope with the complexities. Agile developers often start with the easy cases – and far too often the tough cases get ignored. For example, how does your service work for young people who need additional privacy because of a custody battle currently taking place? Or how does your service work for people with learning difficulties and other additional needs? ??Find the balance between over-engineering processes, but having processes that work for those with the greatest needs, is the key challenge for social innovators.
- Design with social justice in mind – digital innovation in the public sector shouldn’t just be about creating ‘better stuff’ and ‘better services’ for individuals to consume: it should be about creating a ‘better society’ – and that involves thinking about the distribution of benefits from innovation as well as the nature of the innovation itself.
- Collaborate and listen – the most important way to make sure social innovations don’t fall into a Pareto Problem trap is to design with the people working at the frontline.
A metaphorical summary
I started writing this post a while back under the title ‘What happens when we’ve picked all the low hanging fruit?’. Many digital innovations come showing as basket full of the low hanging fruit and explain how easy it was to pick. The key is asking – how are you also planning to get the stuff from the top of the tree as well?
* I’m posting this very tentatively, not sure that I’ve quite managed to express the idea I’ve been reflecting on – but aware that Andy’s paper is currently in progress and that working on the last 20% of tweaks to get this blog post spot on is, um, well, going to take at least four times as long as what’s been written so far… (#paretopost)
** Pareto’s original observations concerned the distribution of wealth in Italy, but the principle has been applied much more widely since. The actual numbers don’t matter here. The 80-20 ratio is simply used because Pareto observed it as a ratio that applied in many real-world situation. Take any ratio in the region of 70-30 towards 99-1 and you will see the argument above still broadly holds.
These are interesting and challenging thoughts.
The starting point must be that we account for a universal service. That should be a simple requirement to recognise – which is not to say either that it is easy to do or that it in practice it is always recognised. The much harder question is then to decide whether a single solution works for the full range of needs and users of the service. Of course the ideal is that it should – but that is where the cost and complexity of managing the final 20% comes in. If a relatively simple digital solution improves service and reduces delivery cost for the 80%, is it wrong if the other 20% see no benefit? What if one result of reducing the unit cost for the 80% is that some of the savings can be used to improve the service for the 20%, but still outside the simple digital solution? It is easy to see those as questions in the sphere of technology or investment management, but they are of course much deeper than that. I see people striving to do good things getting to the point of that dilemma, but then just not having the tools to navigate it. The four approaches you suggest provide a good starting point.
@pubstrat
You raise a really good deeper point here. I don’t see that it matters if we can deliver equal service to 100% of people, with 80% getting the low-cost digital service, and 20% getting extra resources through a different service (for e.g. reality likely to be far more complex / many different services).
The interesting challenge I think, ideologically at least, certainly comes in when the economics mean we can deliver a better service to 80%, but can’t afford it for the last 20% – and the consequence of that may be widening inequality.
I’ve got a #paretopost (think I might use that from now on for posts sitting waiting for that last 20% to be improved…) sitting waiting to be tidied up that tries to explore how Rawl’s Difference Principle applies in this space.
Certainly a big part of the answer I think is also in your recent post. If we better connect designers and developers – we can go some way towards better focussing the limited innovation resources we have available to where they will help most…
digitising for the mainstream is only going to lead to ‘service snagging’ (in the way that mysociety is ‘democracy snagging’).
i think the tricky 20% is the key to unlocking real innovation.
we could apply the international idea of reverse innovation (e.g. From Reverse Innovation to Innovation Blowback) to innovation in an unequal society.
note that this kind of innovation implies efficieny and economic benefit.
if this is catalysed by using codesign lean startup techniques with the hard to reach communities it would handily combines at least 3 of your 4 criteria 🙂
I’m not sure we can continue to think about universal services. What someone with ‘complex’ needs requires may be so different from ‘other’ service users that for them all to go to one (e.g.) social services department and get different versions of the same service seems highly inappropriate.
We need to see a shift to an eco-system or ‘long tail’ of services, and we need service users (though I prefer the term ‘individuals’) to both design and deliver services themselves as. The public sector’s role should be as a supporter of this eco-system.
Are we anywhere near this vision? nope, but a girl can dream 🙂
Hey Carrie
There are at least two senses of ‘universal service’ possible here:
(1) Services in response to a universal ‘entitlement’ (right?) of citizens. A service everyone is entitled to.
(2) Particular service providers being universally responsible for delivering a particular service all people.
I’m defending (1), but not (2), although (2) might be the right thing still in some contexts. There is a question with (1) about whether we should abandon specifying universal entitlement to service (i.e. ‘you are entitled to healthcare for this set of health needs’) with universal entitlement to outcomes (i.e. ‘you are entitled to this level of health’) – but I suspect the second option is far too demanding to fully implement (although some sense of outcome entitlement is valuable…).
In terms of a long-tail of services meeting citizen needs (and I prefer the term citizen to individual – as many of the problems we’re addressing need to be solved through collective, rather than individual, action) this can certainly be a route to ensuring the that all people have their entitlement to a certain level of service fulfilled. But this gives the state two roles: (a) eco-system supporter; creating the conditions in which provision emerges in the long-tail; (b) guarantor or service; filling the gaps.
It feels as though we often get drawn into designing the state that just does (a) and forget about designing for a state that has to do both (a) and (b)…